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1.
Non-stationary spatial covariance structure estimation in oversampled domains by cluster differences scaling with spatial constraints 总被引：2，自引：2，他引：0
J. F. Vera R. Macías J. M. Angulo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(1):95-106
In the analysis of spatiotemporal processes underlying environmental studies, the estimation of the non-stationary spatial
covariance structure is a well known issue in which multidimensional scaling (MDS) provides an important methodological approach
(Sampson and Guttorp in J Am Stat Assoc 87:108–119, 1992). It is also well known that approximating dispersion by a non-metric
MDS procedure offers, in general, low precision when accurate differences in spatial dispersion are needed for interpolation
purposes, specially if a low dimensional configuration is employed besides a high number of stations in oversampled domains.
This paper presents a modification, consisting of including geographical spatial constraints, of Heiser and Groenen’s (Psychometrika
62:63–83, 1997) cluster differences scaling algorithm by which not the original stations but the cluster centres can be represented,
while the stations and clusters retain their spatial relationships. A decomposition of the sum of squared dissimilarities
into contributions from several sources of variation can be employed for an exploratory diagnosis of the model. Real data
are analyzed and differences between several cluster-MDS strategies are discussed. 相似文献
2.
变异函数是地统计学中区域化变量空间结构分析和空间局部插值的主要分析工具.理论变异函数模型的获取是地质统计学中的基础性工作,它是了解区域化变量的变异特征、进一步对地质统计学计算的必要环节.针对现有的理论变异函数的拟合方法,如人工拟合法、线性规划拟合法、加权多项式拟合法、目标规划拟合法等的不足之处,充分利用粒子群优化算法在求解非线性优化问题时具有的全局寻优的特点,提出基于粒子群优化的理论变异函数拟合方法.在实例应用中,分别利用粒子群优化算法和加权多项式拟合方法进行理论变异函数拟合,交叉验证结果表明粒子群优化算法预测精度较高,具有较强的稳健性. 相似文献
3.
Jörg Benndorf Joachim Menz 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(3):627-637
Modern methods of geostatistics deliver an essential contribution to Environmental Impact Assessment (EIA). These methods allow for spatial interpolation, forecast and risk assessment of expected impact during and after mining projects by integrating different sources of data and information. Geostatistical estimation and simulation algorithms are designed to provide both, a most likely forecast as well as information about the accuracy of the prediction. The representativeness of these measures depends strongly on the quality of the inferred model parameters, which are mainly defined by the parameters of the variogram or the covariance function. Available data may be sparse, trend affected and of different data type making the inference of representative geostatistical model parameters difficult. This contribution introduces a new method for best fitting of the geostatistical model parameters in the presence of a trend, which utilizes the empirical and theoretical differences between Universal Kriging and trend-predictions. The method extends well known approaches of cross validation in two aspects. Firstly, the model evaluation is not only limited to sample data locations but is performed on any prediction locations of the attribute in the domain. Secondly, it extends the measure used in cross validation, based on a single point replacement by using error curves. These allow defining rings of influence representing errors resulting from separate variogram lags. By analyzing the different variogram lags the fit of the complete covariance can be assessed and the influence of the several model parameters separated. The use of the proposed method in an EIA context is illustrated in a case study related on the prediction of mining-induced ground movements. 相似文献
4.
Rubén Fernández-Casal Mario Francisco-Fernández 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(5):1247-1259
In geostatistics, the approximation of the spatial dependence structure of a process, through the estimation of the variogram or the covariogram of the variable under consideration, is an important issue. In this work, under a general spatial model, including a mean or trend function, and without assuming any parametric model for this function and for the dependence structure of the process, a general nonparametric estimator of the variogram is proposed. The new approach consists in applying an iterative algorithm, using the residuals obtained from a nonparametric local linear estimation of the trend function, jointly with a correction of the bias due to the use of these residuals. A simulation study checks the validity of the presented approaches in practice. The broad applicability of the procedures is demonstrated on a real data set. 相似文献
5.
Accurate estimation of aquifer parameters, especially from crystalline hard rock area, assumes a special significance for management of groundwater resources. The aquifer parameters are usually estimated through pumping tests carried out on water wells. While it may be costly and time consuming for carrying out pumping tests at a number of sites, the application of geophysical methods in combination with hydro-geochemical information proves to be potential and cost effective to estimate aquifer parameters. Here a method to estimate aquifer parameters such as hydraulic conductivity, formation factor, porosity and transmissivity is presented by utilizing electrical conductivity values analysed via hydro-geochemical analysis of existing wells and the respective vertical electrical sounding (VES) points of Sindhudurg district, western Maharashtra, India. Further, prior to interpolating the distribution of aquifer parameters of the study area, variogram modelling was carried out using data driven techniques of kriging, automatic relevance determination based Bayesian neural networks (ARD-BNN) and adaptive neuro-fuzzy neural networks (ANFIS). In total, four variogram model fitting techniques such as spherical, exponential, ARD-BNN and ANFIS were compared. According to the obtained results, the spherical variogram model in interpolating transmissivity, ARD-BNN variogram model in interpolating porosity, exponential variogram model in interpolating aquifer thickness and ANFIS variogram model in interpolating hydraulic conductivity outperformed rest of the variogram models. Accordingly, the accurate aquifer parameters maps of the study area were produced by using the best variogram model. The present results suggest that there are relatively high value of hydraulic conductivity, porosity and transmissivity at Parule, Mogarne, Kudal, and Zarap, which would be useful to characterize the aquifer system over western Maharashtra. 相似文献
6.
Temporal and spatial rainfall patterns were analysed to describe the distribution of daily rainfall across a medium‐sized (379km2) tropical catchment. Investigations were carried out to assess whether a climatological variogram model was appropriate for mapping rainfall taking into consideration the changing rainfall characteristics through the wet season. Exploratory, frequency and moving average analyses of 30 years' daily precipitation data were used to describe the reliability and structure of the rainfall regime. Four phases in the wet season were distinguished, with the peak period (mid‐August to mid‐September) representing the wettest period. A low‐cost rain gauge network of 36 plastic gauges with overflow reservoirs was installed and monitored to obtain spatially distributed rainfall data. Geostatistical techniques were used to develop global and wet season phase climatological variograms. The unscaled climatological variograms were cross‐validated and compared using a range of rainfall events. Ordinary Kriging was used as the interpolation method. The global climatological variogram performed better, and was used to optimize the number and location of rain gauges in the network. The research showed that although distinct wet season phases could be established based on the temporal analysis of daily rainfall characteristics, the interpolation of daily rainfall across a medium‐sized catchment based on spatial analysis was better served by using the global rather than the wet season phase climatological variogram model. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
7.
为了削弱大气延迟对干涉结果的影响以提高InSAR的测量能力,本文在InSAR大气相位特征分析的基础上,研究了一种新的InSAR大气相位建模与估计方法.首先采用稳健估计确定大气垂直分层部分的模型参数,然后利用基于Matern模型的Kriging插值估计大气紊流部分,最后应用估计的大气垂直分层和紊流资料改正InSAR测量结果.利用覆盖河南义马地区的ASAR数据对本文提出的方法进行了验证,结果表明去除大气影响后,InSAR重建的DEM与参考DEM的高程差异的均方误差由19.5m降至5.3m,精度提高了约72%.同时,改正后的干涉图更合理地揭示了义马矿区的沉降漏斗情况,进一步验证了本文方法的有效性. 相似文献
8.
The variogram is a key parameter for geostatistical estimation and simulation. Preferential sampling may bias the spatial structure and often leads to noisy and unreliable variograms. A novel technique is proposed to weight variogram pairs in order to compensate for preferential or clustered sampling . Weighting the variogram pairs by global kriging of the quadratic differences between the tail and head values gives each pair the appropriate weight, removes noise and minimizes artifacts in the experimental variogram. Moreover, variogram uncertainty could be computed by this technique. The required covariance between the pairs going into variogram calculation, is a fourth order covariance that must be calculated by second order moments. This introduces some circularity in the calculation whereby an initial variogram must be assumed before calculating how the pairs should be weighted for the experimental variogram. The methodology is assessed by synthetic and realistic examples. For synthetic example, a comparison between the traditional and declustered variograms shows that the declustered variograms are better estimates of the true underlying variograms. The realistic example also shows that the declustered sample variogram is closer to the true variogram. 相似文献
9.
This paper introduces an extension of the traditional stationary linear coregionalization model to handle the lack of stationarity. Under the proposed model, coregionalization matrices are spatially dependent, and basic univariate spatial dependence structures are non-stationary. A parameter estimation procedure of the proposed non-stationary linear coregionalization model is developed under the local stationarity framework. The proposed estimation procedure is based on the method of moments and involves a matrix-valued local stationary variogram kernel estimator, a weighted local least squares method in combination with a kernel smoothing technique. Local parameter estimates are knitted together for prediction and simulation purposes. The proposed non-stationary multivariate spatial modeling approach is illustrated using two real bivariate data examples. Prediction performance comparison is carried out with the classical stationary multivariate spatial modeling approach. According to several criteria, the prediction performance of the proposed non-stationary multivariate spatial modeling approach appears to be significantly better. 相似文献
10.
11.
Histogram and variogram inference in the multigaussian model 总被引：1，自引：4，他引：1
Xavier Emery Julián M. Ortiz 《Stochastic Environmental Research and Risk Assessment (SERRA)》2005,19(1):48-58
Several iterative algorithms are proposed to improve the histogram and variogram inference in the framework of the multigaussian model. The starting point is the variogram obtained after a traditional normal score transform. The subsequent step consists in simulating many sets of gaussian values with this variogram at the data locations, so that the ranking of the original values is honored. The expected gaussian transformation and the expected variogram are computed by an averaging operation over the simulated datasets. The variogram model is then updated and the procedure is repeated until convergence. Such an iterative algorithm can adapt to the case of tied data and despike the histogram. Two additional issues are also examined, referred to the modeling of the empirical transformation function and to the optimal pair weighting when computing the sample variogram. 相似文献
12.
Cyclic softening and strength loss of saturated clays during earthquakes is often an important consideration in engineering problems such as slope stability, dam/levee safety, and foundation bearing capacity. This study proposes a simplified procedure for evaluating cyclic softening (amount of strength loss) that may be expected in saturated clays during earthquakes and illustrates how to implement it in engineering analysis. The procedure has two main steps: (1) estimation of an equivalent cyclic shear strain amplitude and associated number of cycles induced in the soil mass by an earthquake; and (2) estimation of softening and strength loss in the soil mass. A key aspect of the proposed procedure is adoption of a strain-based approach to estimate cyclic softening as opposed to the widely used stress-based approach of liquefaction assessments. A threshold strain concept originating from the strain-based approach is first discussed and the development of a procedure is presented subsequently. The proposed procedure provides reasonable, first-order estimates of cyclic softening consistent with the other developed procedures. In addition, the capability of the procedure is demonstrated with two case histories identified as involving cyclic softening of clays. 相似文献
13.
None of the processes of estimation currently available is fully acceptable to the geophysicist. Firstly, they all assume that the variable, be it seismic reflection time, rms velocities, Bouguer anomaly, etc.… is random, amenable to pure statistical considerations, and the processes all disregard the relationships which link the values of the variable in the different points of the domain under investigation. Secondly, they do not provide the geophysicist with any guideline for smoothing his data, as smoothing and estimation are considered two separate operations. Thirdly, they fail to offer a valid criterion of estimation and a measure of the estimation error. The krigeage process overcomes the above mentioned difficulties. It synthesizes the structural or “geostatistical’ characteristics of the variable by using a function called the variogram (variances of the increases of the variable with respect to distance and direction). It smoothes the variable, when necessary, as a function of the “nugget effect’ (value at the origin of the experimental variogram). It yields an optimum estimation of the variable by minimizing the estimation error, and it computes a measure of the reliability of the estimation, the variance of krigeage. The process is demonstrated herein with three examples of variograms on seismic and gravity data and an example of contouring of velocities, reflection times and depths of a productive layer in an oil field, with detection and correction of irregular data, smoothing of velocities, migration of depth points, and display of estimation error. 相似文献
14.
Spatial statistics of clustered data 总被引：7，自引：7，他引：0
Modern spatial statistics techniques are widely used to make predictions for natural processes that are continuously distributed over some convex domain. Implementation of these techniques often relies on the adequate estimation of certain spatial correlation functions such as the covariance and the variogram from the data sets available. This work studies the practical estimation of such spatial correlation functions in the case of clustered data. The coefficient of variation of the dimensionless spatial density of the point pattern of sample locations is suggested as a useful metric for degree of clusteredness of the clustered data set. We show that the common variogram estimator becomes increasingly unreliable with increasing coefficient of variation of the dimensionless spatial density of the point pattern of sample locations. Moreover, we present a modified form of the variogram estimator that incorporates declustering weights, and propose a scheme for estimating the declustering weights based on zones of proximity. Finally, insight is gained in terms of a numerical application of the common and modified methods on piezometric head data collected over an irregular network.Acknowledgments. This work has been supported by grants from the National Institute of Environmental Health Sciences (P42 ES05948-02), the Army Research Office (DAAG55-98-1-0289), and the National Aeronautics and Space Administration (60-00RFQ041). Some of the calculations conducted in support of this work were done on the SGI Origin 2400 at the North Carolina Supercomputing Center, RTP, NC. 相似文献
15.
A digital procedure for ground water recharge and discharge pattern recognition and rate estimation 总被引：3，自引：1，他引：2
A digital procedure to estimate recharge/discharge rates that requires relatively short preparation time and uses readily available data was applied to a setting in central Wisconsin. The method requires only measurements of the water table, fluxes such as stream baseflows, bottom of the system, and hydraulic conductivity to delineate approximate recharge/discharge zones and to estimate rates. The method uses interpolation of the water table surface, recharge/discharge mapping, pattern recognition, and a parameter estimation model. The surface interpolator used is based on the theory of radial basis functions with thin-plate splines. The recharge/discharge mapping is based on a mass-balance calculation performed using MODFLOW. The results of the recharge/discharge mapping are critically dependent on the accuracy of the water table interpolation and the accuracy and number of water table measurements. The recharge pattern recognition is performed with the help of a graphical user interface (GUI) program based on several algorithms used in image processing. Pattern recognition is needed to identify the recharge/discharge zonations and zone the results of the mapping method. The parameter estimation program UCODE calculates the parameter values that provide a best fit between simulated heads and flows and calibration head-and-flow targets. A model of the Buena Vista Ground Water Basin in the Central Sand Plains of Wisconsin is used to demonstrate the procedure. 相似文献
16.
Due to their high aspect ratio fractures are often conceptualized as lower-dimensional structures embedded into the surrounding host matrix. This simplification is typically made within the context of numerical simulation, for the inverse estimation of the matrix-diffusion coefficient from break-through curves or for the derivation of analytical solutions describing flow and transport in a fracture–matrix system. It is generally justified by the so called Lauwerier assumption stating that the transversal dispersion inside the fracture is infinitely fast therefore hampering the formation of gradients across the width of the fracture. In this study we want to verify the applicability of such lower-dimensional modeling. To that end we investigate the occurrence of fracture-scale gradients in a simplified fracture–matrix model by virtue of analytical as well as numerical investigations. The relevant processes modeled are advection, dispersion, matrix diffusion and linear decay. In addition, we also investigate the impact on the inverse estimation of matrix-diffusion coefficients through analytical solutions, which assume a lower-dimensional fracture. Results show that a lower-dimensional modeling of fractures will only lead to errors for early periods of the time-dependent solution. Such errors may however, extent to the steady state if fast radioactive decay is considered. The estimation of the matrix-diffusion coefficient too is affected by the assumption of a lower-dimensional fracture. We see errors as big as 20% for the estimation procedure, the value of which depends on the ratio of the matrix-diffusion vs. the transversal dispersion coefficient. Our analysis suggest that a lower-dimensional representation of fractures is justified for many typical conditions and that special attention must only be paid in a confined number of cases. 相似文献
17.
The restriction of the Babuska–Brezzi stability criteria for the mixed formulation requires non-uniform interpolation of displacement and pore-pressure variables, which complicates the coding in the finite element analysis. This will certainly preclude the use of many otherwise useful elements. A possible solution to overcome this problem introduced earlier by the authors requires a semi-explicit form. However, the effectiveness of the semi-explicit procedure is dependent on the time step length used, which presents difficulties for transient analysis. In this paper, an unconditionally stable staggered implicit-implicit algorithm is developed, which is generalised from the semi-explicit form. For non-uniform mesh configurations, the results indicate a significant improvement compared with those obtained by using the semi-explicit procedure. 相似文献
18.
《Journal of Atmospheric and Solar》1999,61(6):491-504
Introduced almost 40 years ago, the method of optimal interpolation (OI) has been successfully used in various forms for data analysis in meteorology and oceanography. At the same time upper-atmospheric applications of OI and other techniques based on optimal estimation have remained relatively limited. The theory of OI and related methods is reviewed. Properties of optimal estimation relevant to typical problems of data analysis in the upper atmosphere are highlighted. As a specific example, a simple one-dimensional scheme of OI in time is considered. The scheme is devised to address an important problem of the upper-atmospheric data analysis: extraction of periodic (tidal) components from observations covering a fraction of a day. Possible generalizations of the scheme are also briefly discussed. © 1999 Elsevier Science Ltd. All rights reserved. 相似文献
19.
The variogram is one of the most important tools in the assessment of spatial variability and a crucial parameter for kriging. It is widely known that an estimator for the variogram cannot be used as its representator in some contexts because of its lack of conditional semi negative definiteness. Consequently, once the variogram is estimated, a valid family must be chosen to fit an appropriate model. Under isotropy, this selection is carried out by eye from the observation of the variogram estimated curve. In this paper, a statistical methodology is proposed to explore a valid model for the variogram. The statistic for this approach is based on quadratic forms depending on smoothed random variables which gather the underlying spatial variation. The distribution of the test statistic is approximated by a shifted chi-square distribution. A simulation study is also carried out to check the power and size of the test. Reference bands, as a complementary graphical tool, are calculated. An example from the literature is used to illustrate the methodologies presented. 相似文献
20.
We analyze the impact of the choice of the variogram model adopted to characterize the spatial variability of natural log-transmissivity on the evaluation of leading (statistical) moments of hydraulic heads and contaminant travel times and trajectories within mildly (randomly) heterogeneous two-dimensional porous systems. The study is motivated by the fact that in several practical situations the differences between various variogram types and a typical noisy sample variogram are small enough to suggest that one would often have a hard time deciding which of the tested models provides the best fit. Likewise, choosing amongst a set of seemingly likely variogram models estimated by means of geostatistical inverse models of flow equations can be difficult due to lack of sensitivity of available model discrimination criteria. We tackle the problem within the framework of numerical Monte Carlo simulations for mean uniform and radial flow scenarios. The effect of three commonly used isotropic variogram models, i.e., Gaussian, Exponential and Spherical, is analyzed. Our analysis clearly shows that (ensemble) mean values of the quantities of interest are not considerably influenced by the variogram shape for the range of parameters examined. Contrariwise, prediction variances of the quantities examined are significantly affected by the choice of the variogram model of the log-transmissivity field. The spatial distribution of the largest/lowest values of the relative differences observed amongst the tested models depends on a combination of variogram shape and parameters and relative distance from internal sources and the outer domain boundary. Our findings suggest the need of developing robust techniques to discriminate amongst a set of seemingly equally likely alternative variogram models in order to provide reliable uncertainty estimates of state variables. 相似文献